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|Title:||Adaptive techniques used for lifetime estimation of lithium-ion batteries||Authors:||Khayat, Nachaat
|Affiliations:||Faculty of Engineering
Faculty of Engineering
|Issue Date:||2016-01-17||Part of:||2016 3rd International Conference on Electrical, Electronics, Computer Engineering and their Applications, EECEA 2016||Start page:||98||End page:||103||Conference:||International Conference on Electrical, Electronics, Computer Engineering and their Applications, EECEA 2016 ( 3rd : 21-23 April, 2016 : Beirut, Lebanon )||Abstract:||
A review on the different studies made on the lifetime estimation of the Lithium-Ion batteries. As lithium batteries are one off the main components of many instruments nowadays. This paper reviews and summaries the main studies and researches made to estimate the lifetime, the SOC (State-Of-charge) and the SOH (State Of Health - ability of a battery to display its discharge rate over its lifetime) of this battery model. This is a crucial study because the battery end-of-service-lifetime is important to prevent any sudden power shortages. Four adaptive systems will be illustrated in this article, The Accelerated Lifetime testing Method, the Kalman filter, the Artificial Neural Network, the fuzzy logic systems and the accelerated aging tests.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/5925||ISBN:||9781467369428||DOI:||10.1109/EECEA.2016.7470773||Ezproxy URL:||Link to full text||Type:||Conference Paper|
|Appears in Collections:||Department of Electrical Engineering|
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